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Wind farm power curve modeling using adaptive neuro-fuzzy inference systems

Johnson, PL and Negnevitsky, M 2007 , 'Wind farm power curve modeling using adaptive neuro-fuzzy inference systems', paper presented at the the 8th international conference on intelligent technologies, 12-14 Dec 2007, Sydney, Australia.

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Abstract—Wind power is an important renewable energy source which is currently experiencing rapid global growth. As the penetration of wind power into electricity grids increases, the need for accurate modeling and forecasting of this inherently variable source of power becomes essential. In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) approach to wind farm power curve modeling is presented. Results from a case study demonstrate the advantages of defining fuzzy inference system parameters using intuitive IF-THEN rules and initial membership function allocations compared to a purely “black box” ANFIS modeling approach.

Item Type: Conference or Workshop Item (Paper)
Authors/Creators:Johnson, PL and Negnevitsky, M
Keywords: wind power; wind farm power curve; Adaptive Neuro-Fuzzy Inference System (ANFIS)
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